PointPillars: Bad inference result on sample after overfitting on same sample

Hi @zhulf0804 ,

I wanted to ensure the model can memorise a single training example. To do this I set the __len__() method in the Dataset to return 1. When training I printed the data_dict to ensure that the same sample was used for each iteration. Since the dataset length was set to 1, each epoch consisted of a single training step.

I visualised the train curves in tensorboard and as expected, all three losses eventually decreased to 0. Then I wanted to visualise the prediction of the model. For this I used the test.py script. However, when running on the same sample from training (000000.bin) the model produces zero predictions.

If I set the score_thr in pointpillar.py to 0, then I get a lot of predictions but they are obviously all very low confidence.

Any idea where I am going wrong?